Health monitoring, crisis prevention and support for everyday activities represents an emerging field of application at a national level, with particular reference to fragile individuals, the elderly and people with chronic diseases. An important aspect that should be explored by the end of this decade is how the technologies of artificial intelligence, as applied in the health context, might ultimately improve the quality of the current system and whether the work done as part of the efforts now being made is optimised and sufficient to achieve new objectives. In particular, the ability to process large quantities of data will act as a catalyst, triggering an extremely high number of benefits in the health and wellness sector in terms of prevention, diagnosis and individual treatment.

Telemedicine, Artificial Intelligence, Big data and Forecasting Models / Marino, Domenico; Puglisi, Alfio; Andrea, Antonino; Turchi, Maurizio; Miceli, Antonio; Poggia, Giovanni. - (2021), pp. 351-367.

Telemedicine, Artificial Intelligence, Big data and Forecasting Models

Domenico marino
;
2021-01-01

Abstract

Health monitoring, crisis prevention and support for everyday activities represents an emerging field of application at a national level, with particular reference to fragile individuals, the elderly and people with chronic diseases. An important aspect that should be explored by the end of this decade is how the technologies of artificial intelligence, as applied in the health context, might ultimately improve the quality of the current system and whether the work done as part of the efforts now being made is optimised and sufficient to achieve new objectives. In particular, the ability to process large quantities of data will act as a catalyst, triggering an extremely high number of benefits in the health and wellness sector in terms of prevention, diagnosis and individual treatment.
2021
978-84-09-27745-2
TELEMEDICINE; ARTIFICIAL INTELLIGENCE; BIG DATA; FORECASTING MODELS
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/107587
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